Remote sensing systems, such as radar, sonar, lidar, and/or other ranging sensory systems, are often used to assist in navigation by producing data and/or imagery of the environment surrounding a mobile structure, such as imagery representing above-surface and/or subsurface features critical to navigation of a watercraft over a body of water. Conventional remote sensing systems often include a display configured to provide traditionally recognizable remote sensing imagery to a user.
Remote sensing imagery, and particularly imagery comprising aggregations of remote sensor returns received over time, is typically subject to a variety of measurement errors that reduce the reliability of the imagery, particularly as the range to the area being sensed increases. Further, motion of the remote sensing system increases the number, type, and magnitude of the measurement errors, and such errors increase the risk of a user misinterpreting the imagery (e.g., relative ranges, depths, sizes, and other critical distances reflected in the imagery). At the same time, consumer market pressures and convenience dictate easier to use systems that are inexpensive and that produce high quality resulting imagery. Thus, there is a need for an improved methodology to provide highly accurate remote sensing systems, particularly in the context of providing easily calibrated systems configured to produce reliable remote sensing data and/or imagery important to general operation of a mobile structure.